Currently, many systems have been developed to provide map-related data to users. Users can now access map-related data on desktop computers, dedicated GPS devices, and most recently, mobile computing devices (e.g., mobile phones, tablets, smart watches). Each of these devices generally display a traditional map (e.g., a display with cities, roads, etc.) in various formats. For example, mobile devices may present a matrix of map tiles, each tile representing a portion of the map. Current systems allow users to “zoom” in and out of map in order to view larger or smaller areas in less or more detail, respectively. To enable zooming, current systems present tiles of various sizes in order to respond to the requested zoom level.
While early systems focused primarily on driving directions, and thus primarily provided road-level detail, current systems provide additional detail. For example, popular web-based and mobile map applications provide both road detail as well as location-based detail such as businesses, building outlines, and supplemental content from third-party websites (e.g., “reviews” for restaurants).
Notably however, as the amount of information presented in mapping applications continues to increase, the screen “real estate” available for these applications generally either remains constant or grows smaller (in the case of mobile devices). Because of these constraints, mapping applications attempt to filter non-map data (e.g., business data) in order to maximize the use of screen real estate.
One primary technique currently used is to limit the display of business data based on the zoom level and the size of the business (e.g., the square footage of the store). This decision is made based on two factors. First, larger square footage businesses tend to result in expansive “empty” space in a map. Thus adding, for example, the name of the business incurs little or no penalty, even when the map is zoomed out. Second, larger square footage businesses tend to have broader appeal. For example, a nation-wide retailer of general goods has broader appeal than a smaller, specialty store.
However, this technique suffers from the principle drawback of only providing mediocre results to the largest possible number of people. Additionally, current techniques inherently utilize significant amounts of memory in order to provide data that may ultimately be of little use to the user. Especially in mobile computing devices, this overutilization of memory necessarily degrades the performance of the computing device by degrading the performance of the mapping application as well as parasitically degrading the functionality of other applications running on the computing device.
Thus, there exists a need in the art to optimize and personalize the display of content such as labels on a map. Specifically, there exists a need to optimize memory utilization by mapping applications and provide personalized content to users of mapping applications.